1. Statement of the Technical Field
The inventive arrangements concern wireless ad-hoc communications networks. More particularly, the invention relates to a system and method for employing a secondary communications waveform in a wireless ad-hoc communication network to improve various aspects of network performance.
2. Description of the Related Art
Wireless ad-hoc networks are known in the art. They generally include a class of networks in which wireless communications are used to link a plurality of nodes, which can be mobile. Significantly, each node can function as a router and/or as a host. In operation, each node is configured to communicate directly with other nodes (i.e. without the use of a centralized access point). The topology of the ad-hoc network is not fixed and various nodes automatically reconfigure themselves to function as routers on an as needed basis. Packetized data communicated in the network can travel from a source node to a destination node either directly, or through some set of intermediate packet forwarding nodes. Nodes are typically configured to execute a defined neighbor discovery procedure to locate unconnected nodes in the network and determine paths through the network through which data traffic can be communicated from a source node to a destination node. These procedures are well known in the art.
Various ad-hoc networks have been designed for tactical uses. For example, a Highband Networking Waveform (HNW) has been developed to provide core line-of-sight communications capability used in High-Capacity Terrestrial Links (HCTL), High-Capacity Ground-to-Air (HCGA) Links, High Capacity Littoral Links (HCLL) which may be extended-line-of-sight (ELOS), Airborne Cross Links (ACX) and Tactical Relay Links (TRLs). Together with SATCOM links, these line-of-sight links form the core of a battle-space networking transmission subsystem. The HNW is designed to integrate with an IP ad hoc network layer and includes integrated services such as demand-based capacity assignment, neighbor discovery, mobility management, topology management and link state reporting to support the mobile ad hoc network. Physical layer properties in ad-hoc networks such as HNW are implemented primarily through the use of directional antennas and time-division multiple access (DTDMA).
One of the limiting factors for HNW is the level of frequency re-use, or equivalently the number of nodes that may communicate simultaneously within any given timeslot. Frequency re-use is driven by the RF interference measured at any given receive node within a timeslot, which is obtained as a combination of all transmitting nodes, and is a strong function of directional antenna patterns, geographic node topology, and distances. If this cumulative interference is too large at a given receiver, the signal to noise ratio (SNR) of the intended packet(s) sent to a given receiver will be too low to be received correctly. The existing HNW algorithms estimate this signal to interference ratio (SIR), and adjust modulation types used for network communications between phase shift keying (PSK) and quadrature amplitude modulation (QAM) variants in an effort to maximize the overall flow of data. When the network is optimized in this way then, for any given timeslot, the effect of adding an additional transmitting node is to reduce the expected amount of data received correctly during that timeslot.
Chaotic systems can generally be thought of as systems which vary unpredictably unless all of its properties are known. When measured or observed, chaotic systems do not reveal any discernible regularity or order. Chaotic systems are distinguished by a sensitive dependence on a set of initial conditions and by having an evolution through time and space that appears to be quite random. However, despite its “random” appearance, chaos is a deterministic evolution.
Practically speaking, chaotic signals are extracted from chaotic systems and have random-like, non-periodic properties that are generated deterministically and are distinguishable from pseudo-random signals generated using conventional PRNG devices. In general, a chaotic sequence is one in which the sequence is empirically indistinguishable from a digitization of a true random process absent some knowledge regarding the algorithm which is generating the chaos.
Some have proposed the use of multiple pseudo-random number generators to generate a digital chaotic-like sequence. However, such systems only produce more complex pseudo-random number sequences that possess all pseudo-random artifacts and no chaotic properties. While certain polynomials can generate chaotic behavior, it is commonly held that arithmetic required to generate sufficiently large chaotic number sequences requires an impractical implementation due to the precision required.
Communications systems utilizing chaotic sequences offer promise for being the basis of a next generation of low probability of intercept (LPI) waveforms, low probability of detection (LPD) waveforms, and secure waveforms. While many such communications systems have been developed for generating chaotically modulated waveforms, such communications systems suffer from low throughput. The term “throughput” as used herein refers to the amount of data transmitted over a data link during a specific amount of time. This throughput limitation stems from the fact that a chaotic signal is produced by means of a chaotic analog circuit subject to drift.
The throughput limitation with chaos based communication systems can be traced to the way in which chaos generators have been implemented. Chaos generators have been conventionally constructed using analog chaotic circuits. The reason for reliance on analog circuits for this task has been the widely held conventional belief that efficient digital generation of chaos is impossible. Notwithstanding the apparent necessity of using analog type chaos generators, that approach has not been without problems. For example, analog chaos generator circuits are known to drift over time. The term “drift” as used herein refers to a slow long term variation in one or more parameters of a circuit. The problem with such analog circuits is that the inherent drift forces the requirement that state information must be constantly transferred over a communication channel to keep a transmitter and receiver adequately synchronized.
The transmitter and receiver in coherent chaos based communication systems are synchronized by periodically exchanging state information over a data link. Such a synchronization process offers diminishing return because state information must be exchanged more often between the transmitter and the receiver to obtain a high data rate. This high data rate results in a faster relative drift. In effect, state information must be exchanged at an increased rate between the transmitter and receiver to counteract the faster relative drift. Although some analog chaotic communications systems employ a relatively efficient synchronization process, these chaotic communications systems still suffer from low throughput.
The alternative to date has been to implement non-coherent chaotic waveforms. However, non-coherent waveform based communication systems suffer from reduced throughput and error rate performance. In this context, the phrase “non-coherent waveform” means that the receiver is not required to reproduce any synchronized copy of the chaotic signals that have been generated in the transmitter. Further, many non-coherent chaotic waveforms embed additional information in the signal that may be exploited by an unintended receiver to gain partial information of the transmission. The phrase “communications using a coherent waveform” means that the receiver is required to reproduce a synchronized copy of the chaotic signals that have been generated in the transmitter.